Design of a digital model for reserve estimation at the Bled el Hadba phosphate deposit-Birelater, Tebessa

Abstract

Enhancing the economic landscape of a nation and elevating societal well-being hinges on the strategic utilization of mineral resources. This study focuses on optimizing phosphate mining in the Bled el Hadba deposit, located in the Bir Elater region of Tebessa. By leveraging geological data and drilling logs, we analyze mineral distribution, structures, and alterations to pinpoint high-yield areas for sustainable exploitation. Additionally, we highlight the transformative impact of data science on mining operations, revolutionizing decisionmaking processes. Advanced analytical techniques, including modeling and machine learning, enable precise predictions of future performance by considering variables such as ore grade and deposit geometry. The integration of these methodologies not only enhances operational efficiency and profitability but also fosters environmental sustainability. Collaboration between data scientists and geoscience experts facilitates rapid analysis and interpretation of exploration data, propelling innovation in the mineral exploration sector. Our modeling efforts yield spatial layouts depicting grade distributions, laying the foundation for informed decision-making in future exploitation endeavors. This interdisciplinary approach underscores the imperative of synergy between diverse fields, underscoring the potential for collective advancement in mineral resource management.